Jul 29, 2020

BCG: The most innovative companies 2020

Technology
Innovation
Kayleigh Shooter
2 min
lightbulb
We take a look at Boston Consulting Group (BCG)’s list of the most innovative companies of 2020, do you agree with its choices...

 The list contains the most advanced companies who are the strongest at innovation. Only eight companies have been featured in the list every year for the fourteen years that the company has been running the list; Alphabet, Amazon, Apple, HP, IBM, Microsoft, Samsung, and Toyota. 

When research was being conducted for the list, the COVID-19 pandemic was not yet upon us, by the end of the research period, the team found that many of the companies featured were rapidly innovating to overcome the difficult period caused by the pandemic.

The need for innovation and digital transformation is even more prevalent currently in the middle of a pandemic as companies have had to adapt to remote working conditions. Employees rely on emails and messaging to stay in contact with each other, they have also had to adapt to video communication software such as Microsoft Teams or Zoom Communications. 

The need for a digital transformation is extraordinary right now and companies who had previously created a digital transformation strategy are the ones that are better off now.

Among the top flight companies in the list was:

  • Apple
  • Alphabet
  • Microsoft
  • Samsung 
  • Amazon 

Boston Consulting Group has created an interactive graph showing how rankings for the most innovative companies have changed over time, you can find it here.

This year’s comprehensive list of the top fifty most innovative companies focuses on a survey of 2,500 global technology executives, in addition this year, BCG included a new scoring dimension, they incorporated the company’s variety and intensity of boundary-breaking, by assessing its ability to breach established industry entry barriers and play in an array of markets outside its own. 

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Image Credits: Visual Capitalist

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Jun 22, 2021

What is neuromorphic AI?

Intel
neuromorphicai
AI
machinelearning
2 min
Neuromorphic computing – or neuromorphic AI – is the hardware side of artificial intelligence, changing the rules for the future of machine learning

AI is dead. Long live AI?

 

AI is evolving. The first generation of machine learning used ordinary logic and rules to draw conclusions in a very specific manner. A good example would be IBM’s Deep Blue computer, which was trained to play chess to championship standard. That hasn’t disappeared, but it has been augmented by more perceptive deep learning networks that can analyze a broader set of parameters and provide intelligent insights.

 

And neuromorphic AI is next?

 

Correct. Neuromorphic computing is a way of designing hardware – microprocessors, really – to work more like human brains. The idea is that this new iteration of AI hardware will allow machine learning of the future to deal better with ambiguity and contradiction, things that are currently difficult to process for computers.

 

How does neuromorphic AI work?

 

The problem with current chip architecture is that it is not very efficient. Because of the linearity of the process, the chips have to built with a massive amount of horsepower just in case it’s needed. Building a human brain that way would be unfeasible, so engineers have had to rethink the nature of chip design in their quest to get computers to perform more of the tasks human brains are good at. Enter SNNs.

 

What’s an SNN?

 

A spiking neural network (SNN) is, in the words of chipmaker Intel, “a novel model for arranging those elements to emulate natural neural networks that exist in biological brains.” Each ‘neuron’ fires independently, triggering other neurons only when they are required. Intel again: “By encoding information within the signals themselves and their timing, SNNs simulate natural learning processes by dynamically remapping the synapses between artificial neurons in response to stimuli.”

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